Module 13 Wrap-up: The Team Lead
Hands-on: Design the architecture for a multi-agent system that handles a complex business workflow.
Module 13 Wrap-up: The Strategic Leader
You have moved from a "Single AI" mindset to a "Distributed Systems" mindset. You understand that the future of enterprise AI is not one giant brain, but a Team of Specialists overseen by a Planner or Supervisor. This approach is more secure, more reliable, and easier to scale.
Hands-on Exercise: The Content Machine
1. The Scenario
You need to build a system that:
- Researches a trending tech topic.
- Writes a 1,000-word blog post.
- Critiques the post for SEO and clarity.
2. The Task
Draw (or describe) the multi-agent architecture for this.
- Which agent is the Planner?
- Which agent is the Researcher?
- How does the Critique Agent send feedback back to the Writer? (The "Feedback Loop").
Module 13 Summary
- Planner-Executor: Separates strategy from action to reduce confusion.
- Supervisor: Routes tasks to specialized experts.
- Isolation: Keeps sub-agents secure and focused.
- Feedback Loops: Allowing one agent to "Grade" the work of another.
Coming Up Next...
In Module 14, we introduce the most important element of any safe AI: The Human. We will learn about Human-in-the-Loop patterns and how to pause an agent's execution until a real person clicks "Approve."
Module 13 Checklist
- I can explain the benefit of using a fast model for execution and a slow model for planning.
- I understand the Supervisor pattern.
- I know how to share state between two agents.
- I can describe why task delegation is better for security.
- I have identified a workflow that requires at least 3 different specialists.